1. Field
This disclosure relates to processing digital images and, more particularly, to segmenting a digital image.
2. Background Information
In digital image processing systems, a variety of forms of digital image processing operations are performed. At times, the entire image processing system, as well as its individual component operations, depends on the particular application. Nonetheless, a challenge in digital image processing systems at large is to successfully segment a digital image, e.g., to partition the image into a set of smaller and meaningful regions. This is desirable in a plethora of situations. For example, it may be desirable to use different methods to process, transmit or store the different regions of the image depending on the region contents. In video and image communications, if limited bandwidth and/or memory are available it may be interesting or desirable to dedicate more bits to represent the most relevant regions of the image according to some application specific interest metric. A commonly used interest metric in segmentation of such a digital image partitions the image so that regions corresponding to moving objects in the scene, referred to in this context as xe2x80x9cforeground objects,xe2x80x9d are segmented or separated from the static xe2x80x9cbackgroundxe2x80x9d of the scene being imaged. Segmenting the image in this manner, also known as background/foreground segmentation, may be desirable in a host of possible applications. These include, but are not limited to, automated target acquisition and tracking, surveillance applications, navigation applications, gesture interpretation, video-based command and control, and computer games. A computer or similar computing platform may be used to execute such a segmentation method. Well-known segmentation methods based on edge detection generally fail to use the motion information that separates the foreground from the background. Methods that are based on computing a difference between a known shot of the background and the current video frame may produce artifacts known as false negatives (e.g., holes in the moving objects) and false positives (e.g., pieces of background merged with the foreground objects). Processes that are based on elaborate physical models for object dynamics may deliver better segmentation results, but often are too computationally intensive to perform in real-time. A need, therefore, exists for a method or technique for segmenting a digital image that improves upon the state of the art technology for real-time image segmentation.
Briefly, in accordance with one embodiment of the invention, a method of segmenting an initial digital image includes the following. The initial digital image is processed to produce a first digital image with defined edges corresponding to the initial digital image and to produce a second digital image with at least two dominant contiguous regions corresponding to the initial digital image. Distinct non-overlapping regions of the first digital image formed by the defined edges are identified. The distinct non-overlapping regions of the first digital are combined based, at least in part, on a correspondence with the at least two dominant contiguous regions in the second digital image. Based, at least in part, on the remaining regions after combining the distinct non-overlapping regions of the first digital image, the initial digital image is segmented.
Briefly, in accordance with another embodiment of the invention, a method of removing at least some noisy pixels internal to one or more objects in a digital image includes the following. A sequence of one or more morphological openings and/or closings are applied in gradually increasing size. Then, a morphological closing with reduced erosion is applied, the erosion having a size larger than any of the one or more morphological openings and/or closings in the sequence.